- Krishnan Viswanath has over 20 years of experience in technology management focusing on data governance, reference data, and data quality. - Emerging topics in technology include mobile apps, big data, cloud computing, actionable analytics and visualization, data science, the internet of things, and wearable technologies. - Democratization of technology through low-cost platforms like Raspberry Pi, BeagleBone Black, and HummingBoard is enabling more people to learn programming, explore open source operating systems, build autonomous systems and robots, and develop innovative applications.

1. Emerging topics in technology
- Krishnan Viswanath

2. Introduction
Krishnan Viswanath
~20 years of technology experience
Manage Data Governance, Reference Data and
Data Quality technology for Consumer &
Community banking
கற்றது கைகமண் கஅளவ,
கல்லாதது கஉலகளவ

3. Technology – Strategic Advantage
Royal Navy against combined French-Spanish
fleets
Admiral Horatio Nelson
Unconventional strategy & strategic advantage

4. Competitive Advantage
Cost leadership strategy - The goal of cost leadership strategy is to offer products or services at the lowest cost in the
industry. Companies such as Walmart succeed with this strategy by featuring low prices on key items on which customers
are price-aware, while selling other merchandise at less aggressive discounts. Products are to be created at the lowest cost
in the industry.
Differentiation strategy - The goal of differentiation strategy is to provide a variety of products, services, or features to
consumers that competitors are not yet offering or are unable to offer. An example is Dell which launched mass-
customizations on computers to fit consumers' needs. This allows the company to make its first product to be the star of its
sales.
Innovation strategy - The goal of innovation strategy is to leapfrog other market players by the introduction of completely
new or notably better products or services. This strategy is typical of technology start-up companies which often intend to
"disrupt" the existing marketplace, obsoleting the current market entries with a breakthrough product offering. It is harder
for more established companies to pursue this strategy because their product offering has achieved market acceptance.
Apple has been a notable example of using this strategy with its introduction of iPod personal music players, and iPad
tablets. Many companies invest heavily in their research and development department to achieve such statuses with their
innovations or the competition
Operational effectiveness strategy - The goal of operational effectiveness as a strategy is to perform internal business
activities better than competitors, making the company easier or more pleasurable to do business with than other market
choices. It improves the characteristics of the company while lowering the time it takes to get the products on the market
with a great start.

5. 1970's - 80's 1980's 1990's
MP3 Format
Late 90's and early
2000's
Early devices – limited memory
Poor user experience
Lot of illegal downloads
CDs were expensive ($17 - $30)
Competitive Advantage

6. Low End Disruption and
New Market Disruption
Cannibalization
Value Differentiation Strategy

7. Mobile Apps

8. Mobile Apps
Mobile devices overtaking PCs as the most common web access device
worldwide by end of 2013
More market shift towards complex business applications instead of small
niche consumer apps
Similar to PC evolution of desktop productivity apps to network enabled
enterprise solutions
Apple iOS and Google Android will continue to dominate market share for next
few years
Native Apps will continue to be preferred development platform, however,
HTML5/Hybrid will start gaining ground

9. Big Data - NoSQL
Next Generation Databases mostly addressing some of the points: being non-
relational, distributed, open-source and horizontal scalable.
Key factor over SQL databases is its ability to store and retrieve data across
multiple commodity server nodes in parallel
The original intention has been modern web-scale databases.
The mass movement began early 2009 and is growing rapidly. However, core
technology dates back to 1990’s
New York Times
Etsy
Evite
LexisNexis
FlockDB Twitter

10. Big DataBig data is a broad term for data sets so large or
complex that traditional data processing applications
are inadequate. Challenges include analysis, capture,
curation, search, sharing, storage, transfer,
visualization, and information privacy.
A 360 degree view of the customer
Internet of Things
Data warehouse optimization
Security Intelligence Extension
Big Data Exploration
Netflix exploited its Big Data capabilities to influence
its programming choices.
“House of Cards” is one of the first major test cases of
this Big Data-driven creative strategy.
Leverage detailed knowledge of Netflix subscriber
viewing preferences
Decision to license a remake of the popular and
critically well regarded 1990 BBC miniseries.
Netflix’s data indicated that the same subscribers who
loved the original BBC production are likely to
embrace series starring Kevin Spacey or directed by
David Fincher.
The company committed $100 million for two 13-
episode seasons

11. Big Data

Automatically generated by a machine
•
(e.g. Sensor embedded in an engine)

Typically an entirely new source of data
•
(e.g. Use of the internet)

Not designed to be friendly
•
(e.g. Text streams)

May not have much values
•
Need to focus on the important part
Walmart parking lot

12. Big Data Stats

13. Big Data Stats

14. Big Data Technology

15. Cloud Computing
Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a utility (like the
electricity grid) over a network. At the foundation of cloud computing is the broader concept of converged
infrastructure and shared services.

Cloud computing, or in simpler shorthand just "the cloud", also focuses on maximizing the effectiveness of the shared
resources. Cloud resources are usually not only shared by multiple users but are also dynamically reallocated per
demand. This can work for allocating resources to users. For example, a cloud computer facility that serves European
users during European business hours with a specific application (e.g., email) may reallocate the same resources to
serve North American users during North America's business hours with a different application (e.g., a web server). This
approach should maximize the use of computing power thus reducing environmental damage as well since less power,
air conditioning, rack space, etc. are required for a variety of functions. With cloud computing, multiple users can access
a single server to retrieve and update their data without purchasing licenses for different applications.
IAAS – Infrastructure
as Service
RackSpace
Google AppEngine
Azure
Linode
GoGrid
VPS.NET
Voxel
RimuHosting

16. AWS – Amazon Web Services

17. Actionable Analytics & Visualization

While the traditional analytical tools that comprise basic business intelligence (BI) examine historical data, tools for
advanced analytics focus on forecasting future events and behaviors, allowing businesses to conduct what-if analysis to
predict the effects of potential changes in business strategies.

Predictive analytics, data mining, big data analytics, and location intelligence are just some of the analytical categories
that fall under the heading of advanced analytics. These technologies are widely used in industries including marketing,
healthcare, risk management, and economics.

18. Data Science

In general terms, data science is the extraction of knowledge from data. It employs techniques and theories drawn from
many fields within the broad areas of mathematics, statistics, and information technology, including signal processing,
probability models, machine learning, statistical learning, computer programming, data engineering, pattern recognition
and learning, visualization, predictive analytics, uncertainty modeling, data warehousing, and high performance
computing.

Data scientists investigate complex problems through expertise in disciplines within the fields of mathematics, statistics,
and computer science. These areas represent great breadth and diversity of knowledge, and a data scientist will most
likely be expert in only one or at most two of these areas and merely proficient in the other(s).
http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/
http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all

19. Actionable Analytics & Visualization
Healthcare

Researchers at Case Western Reserve University and colleagues used "big data" analytics to predict if a patient is
suffering from aggressive triple-negative breast cancer, slower-moving cancers or non-cancerous lesions with 95
percent accuracy. The work comes just two months after senior author Anant Madabhushi and another group of
researchers showed they can detect differences between persistent and treatable forms of head and neck cancers
caused by exposure to human papillomavirus, with 87.5 percent accuracy. In that study, digital images were made from
slides of patients' tumors.
Drug Store Retail

to help them predict the scope of flu season or allergy season six months in advance so they can more efficiently stock
just the right amount of medication — neither running short nor overstocking and taking up valuable shelf space that
could be dedicated to something else.
Farming

Farms are leveraging advanced analytics to provide more insight into when to plant, how to optimize crop yields and
when to harvest. Manufacturers are turning to advanced analytics to predict when a machine on the production floor is
going to fail so they can perform preventative maintenance before a failure causes expensive unscheduled downtime.

Intelligence Agencies!!

20. Internet of things

The Internet of Things (IoT) is a scenario in which objects, animals or people are provided with unique identifiers and
the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

22. Wearable Technologies

Wearable technology is related to both the field of ubiquitous computing and the history and development of wearable
computers. With ubiquitous computing, wearable technology share the vision of interweaving technology into the
everyday life, of making technology pervasive and interaction friction less.
Search for sixth sense in TED talk

23. DemocratizationRaspberry PI
Satellites
Home Automation
Learn Python
Scratch Programming
Lego Controllers
Minecraft
Stream Movies
Stream Audio
What can I do?
Surf the web
Learn to program
Learn Linux
Play Games
Collect Data
Transmit Data
Weather Balloons
Autonomous Systems
Solar Powered
Time lapse capture
Wireless Access Point
Tor Proxy
Drones
Robots
Computing Clusters
Web Servers

24. Democratization
What is BeagleBone Black?

BeagleBone Black is a low-cost,
community-supported
development platform for
developers and hobbyists. Boot
Linux in under 10 seconds and
get started on development in
less than 5 minutes with just a
single USB cable.

HummingBoard – a small and
powerful, low-cost ARM
computer that ignites the
imagination. The
HummingBoard allows you to
run many open source operating
systems – such as Ubuntu,
Debian and Arch – as well as
Android and XBMC.

Intel and CircuitCo have unveiled their second-
generation MinnowBoard. Single-core,
1.46GHz, 64-bit Intel Atom Processor E3815.
The $129 version includes a dual-core,
1.33GHz, Intel Atom E3825. Board targets the
small and low-cost embedded market and was
designed to appeal to both embedded
developers and the maker community." The
device can be used for "embedded
applications or product development

25. DemocratizationRaspberry PI
Satellites
Home Automation
Learn Python
Scratch Programming
Lego Controllers
Minecraft
Stream Movies
Stream Audio
What can I do with Raspeberry PI?
Surf the web
Learn to program
Learn Linux
Play Games
Collect Data
Transmit Data
Weather Balloons
Autonomous Systems
Solar Powered
Time lapse capture
Wireless Access Point
Tor Proxy
Drones
Robots
Computing Clusters
Web Servers